CAJ | 학술논문

针对目前手写数字难识别并且识别正确率低这一现象，提出了一套基于主成分分析法及贝叶斯分类器的手写数字识别方法。该方案首先利用主成分分析法减小输入数据的维数，而后把降维的数据作为训练过的贝叶斯分类器的输入，从而得到对于输入的手写数字的识别。在 MNIST手写数字数据集上该方法能够达到96.35%的识别率。该仿真结果说明文章提出的手写数字识别策略能够实现对手写数字的高效的识别。
침대목전수사수자난식별병차식별정학솔저저일현상，제출료일투기우주성분분석법급패협사분류기적수사수자식별방법。해방안수선이용주성분분석법감소수입수거적유수，이후파강유적수거작위훈련과적패협사분류기적수입，종이득도대우수입적수사수자적식별。재 MNIST수사수자수거집상해방법능구체도96.35%적식별솔。해방진결과설명문장제출적수사수자식별책략능구실현대수사수자적고효적식별。
To deal with the low discrimination and low accuracy of the hand-written digits,this paper proposed a hand-written digits identification method which is based on the Principal Component Analysis (PCA) and the Bayesian classifier.This scheme employs the PCA to reduces the dimension of the input data,then the dimension-reduced data is regarded as the input for the Bayesian classifier,the result of the classifier is the identified digits.This method achieves the accuracy of 96.35% on the MNIST hand-written digits data set.The case study shows that the hand-written digit identification scheme this paper proposed can identify the hand-written digits effectively.